# Model
extractor_mode = "default"
mask_prob = 0.65
final_dim = 256
latent_temp = [2.0, 0.5, 0.999995]
encoder_layerdrop = 0.05
dropout_input = 0.1
dropout_features = 0.1
dropout = 0.1
attention_dropout = 0.1
encoder_layers = 12
encoder_embed_dim = 768
encoder_ffn_embed_dim = 3072
encoder_attention_heads = 12
feature_grad_mult = 0.1
ema = 0.0
optimizer = "fused_adam"
clip_norm = 25
weight_decay = 0.01
lr_policy = "poly"
lr_poly_power = 1.0
warmup_updates = 32000
max_tokens_valid = 1400000
hourglass_transformer = "[2,(8,4),2]"
fp32_pos_conv = False
conv_pos = 128
conv_pos_groups = 16
activation_dropout = 0.0
activation_fn = 'gelu'
apply_mask = False
layer_norm_first = False
rotary_embeddings = False
mha = 'pyt'
fp32_transformer_layernorm = False
fp32_mha_softmax = False
hourglass_resample = 'naive'
target_glu = False
adam_betas = [0.9, 0.98]
adam_eps = 1e-06
conv_feature_layers = '[(512,10,5)]+[(512,3,2)]*4+[(512,2,2)]+[(512,2,2)]'
conv_bias = False
fp32_conv_norms = False
infonce = True
log_keys = ["prob_perplexity", "code_perplexity", "temp"]
enable_padding = False
normalize = False
sample_rate = 16000
num_batch_buckets = 0
required_batch_size_multiple = 8
num_workers = 6
batch_size_valid = None
batch_size = None
initial_lr_scale = 0.0
final_lr_scale = 0.0
hold_updates = 0
benchmark_epochs_num = 3
cpu = False
use_spectrogram_features = False
spectrogram_feature_stacking = 1
spectrogram_feature_subsampling = 1
spectrogram_window_size = 0.02
spectrogram_window_stride = 0.01
spectrogram_n_filt = 80
quantize_input = False
mask_selection = "static"
mask_other = 0
mask_length = 10
no_mask_overlap = False
mask_min_space = 1
mask_channel_prob = 0.0
mask_channel_before = False
mask_channel_selection = "static"
mask_channel_other = 0
mask_channel_length = 10
no_mask_channel_overlap = False
mask_channel_min_space = 1
num_negatives = 100
cross_sample_negatives = 0
codebook_negatives = 0
logit_temp = 0.1
fp32_cosine_sim = False
quantize_targets = True
latent_dim = 0
latent_vars = 320
latent_groups = 2
quantizer_depth = 1
quantizer_factor = 3
negatives_from_everywhere = False
